Prediction of “Aggregation-Prone” Peptides with Hybrid Classification Approach

Algorithm 2

The BalanceCascade algorithm.

Input: Training dataset , the number of individuals , the number of iterations

(1) Begin

(2)    is the false positive rate (the error rate of misclassifying a majority class

 example to the minority class) that should achieve

(3) For

(4) Creating a subset from negative dataset of by using Bootstrap sampling technique, and

  the number is equal to the

(5) Use the Adaboost with the weak classifiers and corresponding weights to train the

  individual model , the ensemble’s threshold is , i.e.

(6) Adjust such that ’s false positive rate is .

(7) Remove from all examples that are correctly classified by

(8) End for

(9) Output: A single ensemble like:

(10) End